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  • Open Access

    ARTICLE

    APSO-CNN-SE: An Adaptive Convolutional Neural Network Approach for IoT Intrusion Detection

    Yunfei Ban, Damin Zhang*, Qing He, Qianwen Shen

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 567-601, 2024, DOI:10.32604/cmc.2024.055007 - 15 October 2024

    Abstract The surge in connected devices and massive data aggregation has expanded the scale of the Internet of Things (IoT) networks. The proliferation of unknown attacks and related risks, such as zero-day attacks and Distributed Denial of Service (DDoS) attacks triggered by botnets, have resulted in information leakage and property damage. Therefore, developing an efficient and realistic intrusion detection system (IDS) is critical for ensuring IoT network security. In recent years, traditional machine learning techniques have struggled to learn the complex associations between multidimensional features in network traffic, and the excellent performance of deep learning techniques,… More >

  • Open Access

    ARTICLE

    Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

    S. Lakshmi Narayanan*

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 931-946, 2022, DOI:10.32604/csse.2022.022459 - 09 May 2022

    Abstract The main aim of this work is to improve the security of data hiding for secret image sharing. The privacy and security of digital information have become a primary concern nowadays due to the enormous usage of digital technology. The security and the privacy of users’ images are ensured through reversible data hiding techniques. The efficiency of the existing data hiding techniques did not provide optimum performance with multiple end nodes. These issues are solved by using Separable Data Hiding and Adaptive Particle Swarm Optimization (SDHAPSO) algorithm to attain optimal performance. Image encryption, data embedding,… More >

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